MOLDEX: A Computer System for Drug Design.
4) A Combined Electro-Geometric Method for theIdenti cation of Pharmacophoric Structural Patterns inDrugs
Hiromi Nakatakenakatake@translell.eco.tut.ac.jp

Carlos Adriel Del Carpio

carlos@translell.eco.tut.ac.jp

Laboratory for Informatics & AI in Moleclular and Biological Sciences
Department of Ecological Engineering. Toyohashi University of Technology
Tempaku, Toyohashi 441-8580, Japan

1 Introduction
In the present study we propose a methodology to extract information on common bioactive as well
as pharmacophoric structural patterns from series of organic molecules recognized as candidate ligand
molecules, or with known bioactive pro les. The methodology is based on a combined 3D structuralsimilarity calculation algorithm and the analysis of the electrostatic potential generated by the common
patterns within the structural environment of each organic compound. The results of the analysis leadto classi cation of ligands into categories re ecting the capacity of interaction of each molecule andeventually features of the ligands related to their agonist or antagonist character. Moreover, theanalysis leads to a simpler docking process whenever the receptor is known or to its portrayal whenthat is not the case.

2 Methodology
Recently we have been developing a system for the automatization of processes of drug design. Oursystem, MOLDEX (MOLecular DEsign X) [3], has as main characteristic modules for mapping receptor
regions on proteins, docking ligand molecules into a receptor region, a module for conformation analysis
in solution, and the modules for two and three dimensional QSAR. Here we describe a new methodology
to extract common 3D structural patterns in series of analogous organic compounds, and the analysisof their electrostatic characteristics within the environment of each particular molecule in order toassess strength and mode of interaction with the receptor.
The major problem in geometrical comparisons of 3D structures of chemical compounds is nding a transformation matrix to superimpose in the most optimal way two three dimensional bodies.
Translational components can however be removed from the transformation matrix by referring themolecules to be compared to their mass centers. The rotation component of the matrix can be foundby approaches in the literature such as the W. Kabsch method [1] or the A.L. Mackay method [4].
These approaches are however limited to the simplest two molecular case. In the present study we haveembedded these algorithms into the genetic algorithm (GA) paradigm to obtain common 3D structural
patterns for more than two molecules. The need for a heuristic method to select the referential pointsof superimposition which yield the optimal RMS value among the structures makes of the GA themost appropriate approach to solve the problem. Pharmacophoric and/or bio-active patterns among
the structures compared are obtained as those where the superimposition of the molecules gives theleast RMS value.
To further analyze the electrostatic characteristics of the fragments obtained by the procedure
above, we have implemented a new methodology based on the mapping of the electrostatic characteristics of the molecules constituting the set. Atomic charges for the atoms constituting the molecules378are computed using the MOPAC system. Electrostatic potentials are calculated at every point of animaginary grid on the molecular surface where an imaginary probe charge of +1u.e. is placed. Theresulting three dimensional distribution of the electrostatic potential so calculated is mapped into a
two dimensional plot by means of the SOM algorithm [2]. Analysis performed on the 2D map ofelectrostatic characteristics of the molecule allows the evaluation of the electrostatic activities of thecommon 3D fragments within di erent chemical environments. Thus reactivities and/or interaction
capabilities for each compound can be readily derived from this analysis.

3 Results and Discussion
We have applied the algorithm discussed in the previous section to a set of three structures known toreact with the benzodiazepine receptor. Fig. 1. shows the molecular formuli of the compounds andillustrates the results of the algorithm, which shows as common fragment the one with the numberedregion on the molecules.
Analysis of the electrostatic characteristics (not shown here) of the common fragment within thechemical environment of the three molecules shows a stronger interaction capability for molecule 1,
while molecule 3 would be the one with the weaker reactive abilities.
These results are of the major relevance in processes where several candidate ligand molecules aregenerated as probable agonists or antagonists to a determined receptor molecule. Furthermore, thepresent methodology can very well be applied to mimetics of organic or bio-molecules.

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2.CINFigure 1: Identi cation of the pharmacophore pattern in benzodiazepine-recepter ligands by molecularstructure superposition. (Ligands: CGS 1 , CIN 2 , TZPH 3 ).

References[1] Kabsch, W., A Discussion of the Solution for the Best Rotation to Relate Two Sets of Vectors,Acta Cryst., A34:828{829, 1978.
[2] Kohonen, T., The self-organizing map, Proceedings of the IEEE, 78:1464{1480, 1990.
[3] Nishimura, K. and Del Carpio, C.A., MOLDEX: A Computer System for Drug Design. 3) Constructing Hypothetical Ligand Molecules, Genome Informatics 1997, Universal Academy Press,
314{315, 1997.
[4] Mackay, A.L., Quaternion Transformation of Molecular Orientation, Acta Cryst., A40:165{166,1984.
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